恶劣天气下的仿生偏振定向方法

针对偏振光导航在恶劣天气下精度显著下降的问题,提出了一种可以在恶劣天气下基于大气偏振模式的定向算法。与现有方法相比,首次将三维块匹配与canny边缘检测结合的思想应用于修复被不同天气破坏的偏振角度图像中。具体而言,将偏振角度图像的修复分为噪声粗处理和边缘提取处理去噪两部分。在噪声粗处理阶段采用三维块匹配算法,在边缘提取处理去噪部分,利用canny边缘检测算法对偏振角度图像进行二次去噪。实验结果表明,该方法不仅能够提高晴朗天空下的定向精度,而且能够显著提升在阴天、沙尘、雾霾等恶劣天气条件下的导航定向精度,即使在偏振角图像对称∞模式被破坏的情况下,航向角精度仍可由9.4470°提高到1.6859°。

Bionic Polarization Orientation Method Under Severe Weather

Aiming at the problem that the accuracy of polarized light navigation decreases significantly in severe weather,a directional algorithm based on atmospheric polarization mode is proposed in severe weather.Compared with existing methods,the idea of combining 3D block matching and canny edge detection is firstly applied to repair the polarization angle images damaged by different weather.Specifically,the restoration of the polarization angle image is divided into two parts:rough noise processing and edge extraction processing denoising.The 3D block matching algorithm is applied in the stage of rough noise processing.In the edge extraction processing denoising part,the canny edge detection algorithm is used to denoise the polarization angle image.Experimental results show that the proposed method can not only improve the orientation accuracy under clear skies,but also significantly improve the navigation orientation accuracy under severe weather conditions such as sandstorm,smog,and overcast sky.Even when the symmetry∞mode of the polarization angle image is destroyed,the accuracy of the heading angle can still be improved from 9.4470°to 1.6859°.